Study Overview

The Connectomes Related to Anxiety and Depression in Adolescents Project is a collaborative effort among researchers at the Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), McLean Hospital, and Boston University. We will focus on understanding psychiatric disorders in adolescence, in particular those associated with two leading causes of death in adolescents and young adults (suicide and substance-abuse related accidents). Our research is guided by the “Acute Threat/Fear” and the “Reward/Prediction Error” construct.

Aude Henin, Ph.D. - MGH

Stefan Hofmann, Ph.D. - BU

Nicholas Hubbard, Ph.D. - MIT

Diego Pizzagalli, Ph.D. - McLean

Anastasia Yendiki, Ph.D. - MGH

Study Protocol Overview

Data being collected

All imaging will be conducted at Massachusetts General Hospital on one of three scanners: A 3T Siemens Prisma, 3T Siemens ConnectomA, and 7T Siemens. A limited version of the HCP Lifespan scanning protocol will be implemented with the intent of keeping the total MR scanning time to under 2 hours.

Standard HCP demographics.

Imaging: The imaging modalities are structural, diffusion, and functional (both resting state and task) with the following tasks: emotion processing, incentive processing, social cognition, working memory/category-specific representations.

The emerging field of 'predictive analytics in mental health' has recently generated tremendous interest with the bold promise to revolutionize clinical practice in psychiatry paralleling similar developments in personalized and precision medicine. Here, we provide an overview of the key questions and challenges in the field, aiming to (1) propose general guidelines for predictive analytics projects in psychiatry, (2) provide a conceptual introduction to core aspects of predictive modeling technology, and (3) foster a broad and informed discussion involving all stakeholders including researchers, clinicians, patients, funding bodies and policymakers.

Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression.

Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression.

Brain connectomics predict response to treatment in social anxiety disorder.

Despite growing evidence for atypical amygdala function and structure in major depression, it remains uncertain as to whether these brain differences reflect the clinical state of depression or neurobiological traits that predispose individuals to major depression. We examined function and structure of the amygdala and associated areas in a group of unaffected children of depressed parents (at-risk group) and a group of children of parents without a history of major depression (control group). Compared to the control group, the at-risk group showed increased activation to fearful relative to neutral facial expressions in the amygdala and multiple cortical regions, and decreased activation to happy relative to neutral facial expressions in the anterior cingulate cortex and supramarginal gyrus. At-risk children also exhibited reduced amygdala volume. The extensive hyperactivation to negative facial expressions and hypoactivation to positive facial expressions in at-risk children are consistent with behavioral evidence that risk for major depression involves a bias to attend to negative information. These functional and structural brain differences between at-risk children and controls suggest that there are trait neurobiological underpinnings of risk for major depression.

Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience.

Neuroimaging has greatly enhanced the cognitive neuroscience understanding of the human brain and its variation across individuals (neurodiversity) in both health and disease. Such progress has not yet, however, propelled changes in educational or medical practices that improve people's lives. We review neuroimaging findings in which initial brain measures (neuromarkers) are correlated with or predict future education, learning, and performance in children and adults; criminality; health-related behaviors; and responses to pharmacological or behavioral treatments. Neuromarkers often provide better predictions (neuroprognosis), alone or in combination with other measures, than traditional behavioral measures. With further advances in study designs and analyses, neuromarkers may offer opportunities to personalize educational and clinical practices that lead to better outcomes for people.

Selective development of anticorrelated networks in the intrinsic functional organization of the human brain.

We examined the normal development of intrinsic functional connectivity of the default network (brain regions typically deactivated for attention-demanding tasks) as measured by resting-state fMRI in children, adolescents, and young adults ages 8-24 years. We investigated both positive and negative correlations and employed analysis methods that allowed for valid interpretation of negative correlations and that also minimized the influence of motion artifacts that are often confounds in developmental neuroimaging. As age increased, there were robust developmental increases in negative correlations, including those between medial pFC (MPFC) and dorsolateral pFC (DLPFC) and between lateral parietal cortices and brain regions associated with the dorsal attention network. Between multiple regions, these correlations reversed from being positive in children to negative in adults. Age-related changes in positive correlations within the default network were below statistical threshold after controlling for motion. Given evidence in adults that greater negative correlation between MPFC and DLPFC is associated with superior cognitive performance, the development of an intrinsic anticorrelation between MPFC and DLPFC may be a marker of the large growth of working memory and executive functions that occurs from childhood to young adulthood.

NIH Blueprint for Neuroscience Research

The Human Connectome Project and Connectome Coordination Facility are funded by the National Institutes of Health,
and all information in this site is available to the public domain. No Protected Health Information has been
published on this site. Last updated 05/19/2016 15:50:08.

Privacy Statement

The member universities of the Human Connectome Project take privacy very seriously, whether dealing with participant data or the data of those visiting this website.

The participant data from our research into the Human Connectome that is stored in our XNAT server is de-identified, and contains no personal health information (PHI).

Our website collects names and email addresses via our contact form. This information is used solely by the administrators and members of the HCP website and is not shared, traded or sold to third parties under any circumstances.

Our website may also collect non-personal data about site visits, sessions, and IP addresses. This information is only used for diagnostic or debugging purposes, to help us optimize our website's performance, and is not shared externally. This is a standard practice for most websites, and this data is never linked with personally identifiable information.

This website contains links to other websites whose content we think is relevant. However, the HCP website is not responsible for maintaining or updating the content of these other sites. If any of these sites are found to contain irrelevant or offensive information, please contact us.

By using humanconnectome.org, you signify your agreement to our privacy policy as stated above. Note that this policy may be revised periodically without notice. Please re-read this policy prior to submitting any personal information if you have concerns about how your information is being collected and used.